Artificial intelligence–based accurate myocardial infarction mapping using 12-lead electrocardiography
The AI-MI-12ECG trained using the biosimulation model in post-MI patients was adequately aligned with CMR-LGE. This highlights its potential for accurate detection of fibrosis and identification of individuals with significant infarct burdens.
Authors
- Lei Xu (ORCID: https://orcid.org/0000-0002-8499-0448)
- Zhifan Gao (ORCID: https://orcid.org/0000-0002-1576-4439)
- Koen Nieman (ORCID: https://orcid.org/0000-0002-8312-0598)
- Heye Zhang (ORCID: https://orcid.org/0000-0003-3828-0629)
- Kairui Bo
- Cuiyan Wang (ORCID: https://orcid.org/0000-0001-8612-5194)
- Zhen Zhou (ORCID: https://orcid.org/0000-0002-0835-8686)
- Hui Wang (ORCID: https://orcid.org/0000-0002-8549-3398)
- Xinwei Zhang (ORCID: https://orcid.org/0000-0002-1267-5182)
- Yuzhen Zhu
- Yifeng Gao (ORCID: https://orcid.org/0009-0005-0103-3837)
- Baiyan Zhuang (ORCID: https://orcid.org/0000-0003-3054-5514)
- Shichang Lian (ORCID: https://orcid.org/0009-0004-6757-6212)
- Shuang Li (ORCID: https://orcid.org/0000-0002-1084-8887)
Institutions
- Sun Yat-sen University (CN)
- Cardiovascular Institute of the South (US)
- Linyi People's Hospital (CN)
- Shandong Provincial Hospital (CN)
- Beijing Anzhen Hospital (CN)
- Stanford Medicine (US)
- Shandong First Medical University (CN)
- Stanford University (US)
Publication Details
- Journal
- European Heart Journal - Digital Health
- Published
- 2025-06-28
- DOI
- https://doi.org/10.1093/ehjdh/ztaf077
- Citations
- 1
- Primary Topic
- Cardiac Imaging and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China